ArchaeoPhases: Post-Processing of the Markov Chain Simulated by 'ChronoModel', 'Oxcal' or 'BCal'

Provides a list of functions for the statistical analysis of archaeological dates and groups of dates. It is based on the post-processing of the Markov Chains whose stationary distribution is the posterior distribution of a series of dates. Such output can be simulated by different applications as for instance 'ChronoModel' (see <https://chronomodel.com/>), 'Oxcal' (see <https://c14.arch.ox.ac.uk/oxcal.html>) or 'BCal' (see <https://bcal.shef.ac.uk/>). The only requirement is to have a csv file containing a sample from the posterior distribution. Note that this package interacts with data available through the 'ArchaeoPhases.dataset' package which is available in a separate repository. The size of the 'ArchaeoPhases.dataset' package is approximately 4 MB.

Version: 1.5
Depends: R (≥ 3.5.0), coda, hdrcde
Imports: stats, utils, graphics, grDevices, shiny, shinythemes, DT, readr, ggthemes, toOrdinal, ggplot2, ggalt, reshape2, dplyr, digest, gplots, magrittr, tibble
Suggests: knitr, rmarkdown, testthat (≥ 2.1.0), ArchaeoPhases.dataset (≥ 0.1.0)
Published: 2020-12-01
Author: Anne Philippe [aut, cre], Marie-Anne Vibet [aut], Thomas S. Dye [ctb]
Maintainer: Anne Philippe <anne.philippe at univ-nantes.fr>
BugReports: https://github.com/ArchaeoStat/ArchaeoPhases/issues
License: GPL-3
NeedsCompilation: no
Citation: ArchaeoPhases citation info
Materials: README NEWS
CRAN checks: ArchaeoPhases results

Downloads:

Reference manual: ArchaeoPhases.pdf
Vignettes: 3.ArchaeoPhases: Analysis of groups of dates
1.ArchaeoPhases : Introduction
2.ArchaeoPhases : Analysis of a series of dates
Package source: ArchaeoPhases_1.5.tar.gz
Windows binaries: r-devel: ArchaeoPhases_1.4.5.zip, r-release: ArchaeoPhases_1.4.5.zip, r-oldrel: ArchaeoPhases_1.4.5.zip
macOS binaries: r-release: ArchaeoPhases_1.4.5.tgz, r-oldrel: ArchaeoPhases_1.4.5.tgz
Old sources: ArchaeoPhases archive

Reverse dependencies:

Reverse depends: ArchaeoChron
Reverse imports: BayLum

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